Gleason score on biopsy: is it reliable for predicting the final grade on pathology?
Bibliographic record
Abstract
OBJECTIVE: To assess the correlation of the Gleason score on biopsy and the final pathology after radical prostatectomy (RP) for prostate adenocarcinoma. PATIENTS AND METHODS: In a retrospective analysis within a tertiary-care centre, the charts of 537 patients who had undergone radical prostatectomy from April 1989 to November 2000 were reviewed. The RPs were undertaken in one institution; 167 biopsies were taken and interpreted in the referring centres, and 355 were taken and interpreted in the authors' institution by up to 15 pathologists. All the final pathology specimens were interpreted by the same group of pathologists. The main outcome measures were: the pathological report of the biopsy including the primary and secondary Gleason grade; the final pathological grade (primary and secondary); the margin status; and the identification of the pathologist for the biopsy and final pathology. RESULTS: In all, 390 patients had inclusion criteria (the Gleason grade before and after RP) available. For the individual scores 38.2% of tumours were undergraded, 32.6% overgraded and only 29.2% had identical grading in preoperative biopsies and final specimens. When grouped into more meaningful categories (Gleason 2-4, 5-6, 7 and 8-10) the correlation improved, with 48.5% of patients remaining in the same group after RP. For 39 patients the same pathologist assessed the biopsy and final specimen; in these cases individual scores were identical in 49% and group scores were identical in 64%. CONCLUSION: Gleason grading of the prostate biopsy remains a poor predictor of pathological outcome. Assessment by the same pathologist reduces the discrepancy but over half the patients are under- or overgraded on final pathology. Clinicians should be aware of these limitations when using the biopsy Gleason grade in decision making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".